SCIENCE CHINA Life Sciences, Volume 64 , Issue 5 : 766-783(2021) https://doi.org/10.1007/s11427-020-1788-2

Gut microbiome alterations and its link to corticosteroid resistance in immune thrombocytopenia

Yanan Wang 1,2,3,†, Fengqi Liu 1,2,3,†, Gaochao Zhang 1,2,3, Yan Su 1,2,3, Xueyan Sun 1,2,3, Qi Chen 1,2,3, Chencong Wang 1,2,3, Haixia Fu 1,2,3, Yun He 1,2,3, Xiaolu Zhu 1,2,3, Xiao Liu 1,2,3, Meng Lv 1,2,3, Xiangyu Zhao 1,2,3, Xiaosu Zhao 1,2,3, Yueying Li 4,5, Qianfei Wang 4,5,6, Xiaojun Huang 1,2,3, Xiaohui Zhang 1,2,3,*
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  • ReceivedJun 2, 2020
  • AcceptedAug 3, 2020
  • PublishedAug 25, 2020



Beijing Municipal Science and Technology Commission(Z171100001017084)

Natural Science Foundation of Beijing Municipality(7171013,H2018206423)

Key Program of National Natural Science Foundation of China(81730004)

the National Natural Science Foundation of China(81670116,81970113)

and National Key Research and Development Program of China(2017YFA0105503)


This work was supported by Beijing Municipal Science and Technology Commission (Z171100001017084), Natural Science Foundation of Beijing Municipality (7171013 and H2018206423), Key Program of National Natural Science Foundation of China (81730004), the National Natural Science Foundation of China (81670116 and 81970113), and National Key Research and Development Program of China (2017YFA0105503).

Interest statement

The author(s) declare that they have no conflict of interest.

Supplementary data


The supporting information is available online at https://doi.org/10.1007/s11427-020-1788-2. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.


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  • Figure 1

    Gut microbial alterations in ITP individuals. Comparison between treatment-naïve ITP patients (n=49) and healthy controls (n=52). A, Rarefaction curves were constructed with 97% sequence similarity at species level. B, The number of annotated species showed no difference between the two groups (P>0.05). C and D, α-Diversity (Shannon index) of the two groups at the gene level (P>0.05) and the species level (P>0.05). E and F, β-Diversity (Bray distance) of the two groups at the gene level (P<0.05) and the species level (P<0.001). G, The distribution of P values. The genes whose median abundances in two cohorts were both less than 10−7 were filtered. After filtering, Wilcoxon rank-sun test was applied to identify the differentially abundant genes. Frequency histogram shows the P value distribution of all genes tested in the two groups. H, The PCA was built using the genes that differed significantly between treatment-naïve ITP patients and healthy controls (false discovery rate (FDR), 0.0001, Wilcoxon rank-sum test adjusted for multiple testing). Forty-nine patients with treatment-naïve ITP are in red, and 52 healthy controls are in blue. I, The of Bacteroidetes/Firmicutes ratio in healthy controls and treatment-ITP patients was similar (the P value shows no obvious significance). For the box plot, Two-tailed Wilcoxon rank-sum test was used to determine significance; boxes represent the interquartile ranges (IQRs) between the first and third quartiles, and the line inside the box represents the median; whiskers represent the lowest or highest values within 1.5 times IQR from the first or third quartiles. “+” represent data point beyond the whiskers. The notches show the 95% confidence interval for the medians.

  • Figure 2

    Differences in phylogenetic abundance between treatment-naïve ITP patients and healthy controls. A, B and D, The phylotypes that were increased in the treatment-naïve ITP patients at the phylum level, genus level and species level. Red and blue indicate the ITP patients and healthy controls, respectively. C and E, The phylotypes that were decreased in the treatment-naïve ITP patients at the genus level and species level. The phylogenetic abundance of phyla that had mean values less than 1% and that of genera and species that were less than 0.01% were excluded. After exclusion, Wilcoxon rank-sum tests were applied to identify the differentially abundant phyla, genera, and species. Among these, the highest medians of the phylogenetic abundance in the enriched cohort were drawn as boxplots.

  • Figure 3

    Correlation between gut species and ITP-related clinical indices, and trial classification of ITP using gut microbial markers. A, The abundance of gut species differed between treatment-naïve ITP patients and healthy controls were analyzed for covariation with clinical variables using Spearman’s correlation coefficient. Species and phenotypes in the heatmap were ordered using unsupervised hierarchical clustering. B and C, The area under the ROC curve (AUC) of gut-microbiota-based ITP classification. A classifier to identify treatment-naïve ITP patients was constructed using 12 gut microbial markers selected by random forest model. The AUC based the classifier is shown for the training and test samples. D and E, The AUC of ITP-associated MGS classification. A classifier based on 22 MGSs selected by random forest model was constructed. The AUC based the classifier is shown for the training and test samples. The gray bars denote the 95% confidence interval (CI) and the area between the two outside curves represents the 95%CI shape. Abbreviations: WBC: white blood cell count; LDL: low density lipoprotein; BMI: body mass index; HDL: high density lipoprotein; ALT: alanine aminotransferase; AST: aspartate aminotransferase; +, P<0.05; *, P<0.01; #, P<0.001.

  • Figure 4

    Co-occurrence network deduced from 69 MGSs enriched in treatment-naïve ITP patients and healthy controls. MGSs were colored according to the phylum they were annotated to. Sizes of the nodes represent the number of genes in the MGSs (700–7,099). Red edges, Spearman’s rank correlation coefficient>0.6, adjusted P<0.05; blue edges, Spearman’s rank correlation coefficient<−0.3, adjusted P<0.05. Unclassified MGSs could not be annotated to any taxonomic level as a result of the low gene annotation. The numbers in parentheses next to each species name represent unique MGS identifiers.

  • Figure 5

    Functional characterization of the treatment-naïve ITP microbiome. The relative abundances of KEGG pathways (A) and modules (B) were compared between treatment-naïve ITP patients and healthy controls (ITP, n=49; healthy controls, n=52). KEGG pathways or modules with reporter scores>1.65 or <−1.65 are shown. Blue and red colors represent healthy control- and ITP-enriched pathways or modules, respectively.

  • Figure 6

    Prediction of the effects of ITP medication on the gut microbiome by random forest classifiers. A–D, Random forest classifiers were used to separate the gut microbiomes of Drug+ ITP patients, Drug− ITP patients and healthy controls, and receiver operating characteristic (ROC) curves are shown for corticosteroid, danazol, TPO/TPO-RA and amino-polypeptide. Ten-fold cross-validation with a random forest classifier was performed ten times. Red curve, Drug− patients versus Drug+ patients. Green curve, Drug− patients versus controls. Blue curve, Drug+ patients versus controls. E, The area under the curve (AUC) and 95%CI are shown.

  • Figure 7

    Gut microbiome alterations in corticosteroid-resistant ITP patients. A and B, Phylogenetic abundance at genus level and species level between corticosteroid-resistant and corticosteroid-sensitive ITP patients and healthy controls. Boxes represent the median and interquartile ranges (IQRs) between the first and third quartiles; whiskers represent the lowest or highest values within 1.5 times IQR from the first or third quartiles. “o” represents all data points. C and D, The relative abundances of KEGG pathways and modules were compared between corticosteroid-resistant and corticosteroid-sensitive ITP. KEGG pathways and modules with reporter scores>1.65 or <−1.65 are shown.


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